Imaging and tracking systems typically include sensors to identify and track objects. For example, some sensors, such as radar systems, send out signals that reflect from objects and are received by the system. Other sensors, such as electro-optical sensors, receive electromagnetic radiation signals from the objects themselves. Improvements in this field have been directed to refining these sensors to be more accurate.
In particular, electro-optical sensors typically use telescopes and focal plane arrays that detect infrared radiation. Suppression of fixed pattern noise (FPN) is one area of development in electro-optical sensors. Generally, calibration or non-uniformity correction has been used to suppress fixed pattern noise. However, this method of fixed pattern suppression may leave a large residual fixed pattern which limits sensor performance and increases sensor noise levels, especially when the raw imagery contains harsh clutter. In addition, there may be instances when calibration cannot be performed prior to use, and the system must be used in a moment's notice. Moreover, tracking objects using an optical sensor with a telescope and focal plane array on a moving platform presents additional problems, such as, a need to compensate for the movement of the moving platform.
Techniques have been developed to remove FPN in video imagery from imaging and tracking systems, and many of these techniques work quite well for uncluttered or mildly-cluttered imagery. But it may be desirable to have an apparatus and method that improves upon these techniques for imagery with harsher clutter.